{"id":"W2143093088","doi":"10.1093/bioinformatics/btp378","title":"ISOLATE: a computational strategy for identifying the primary origin of cancers using high-throughput sequencing","year":2009,"lang":"en","type":"article","venue":"Bioinformatics","topic":"Cancer Diagnosis and Treatment","field":"Medicine","cited_by":40,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Computational biology; Biology; Profiling (computer programming); Sample size determination; Gene expression profiling; Computer science; Gene; Machine learning; Artificial intelligence; Gene expression; Genetics; Statistics; Mathematics","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001159072,0.0001021551,0.0002175869,0.00004954506,0.00009834449,0.00002846557,0.00005317491,0.00003811009,0.00001160481],"category_scores_gemma":[0.00001099087,0.00006969494,0.00008574812,0.0001279479,0.00003922358,0.0001508972,0.00001074507,0.00005703007,0.000001993457],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006758781,"about_ca_system_score_gemma":0.0006229456,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000270394,"about_ca_topic_score_gemma":0.00001489992,"domain_scores_codex":[0.9991828,0.000005492888,0.0003798431,0.00007120184,0.0002022095,0.0001584388],"domain_scores_gemma":[0.9994364,0.00007531999,0.0001985023,0.0001376657,0.0001102761,0.00004187303],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.001197036,0.0007835536,0.00671238,0.007389808,0.002081859,0.00004538242,0.02401248,0.6122601,0.005947854,0.05517421,0.01341823,0.2709771],"study_design_scores_gemma":[0.008369695,0.001978369,0.04408246,0.001624939,0.001082885,0.0001879906,0.00483309,0.9244944,0.004485838,0.006961489,0.001387637,0.0005112335],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9098127,0.0008766053,0.08567131,0.000693378,0.0002843234,0.001339585,0.0001070496,0.00004861254,0.001166359],"genre_scores_gemma":[0.9269885,0.00006707738,0.07206396,0.0007043493,0.00008348381,0.00001267802,0.00005351969,0.000007286812,0.00001916694],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.3122343,"threshold_uncertainty_score":0.2842077,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.09569313300894752,"score_gpt":0.3525244095334745,"score_spread":0.256831276524527,"validation_status":"score_only:v0-immature-baseline","note":"Baseline scores from an immature model (maturity gate not passed). Scores rank; they never assert a category."}}